Researchers at the Oak Ridge National Laboratory (ORNL), in collaboration with three other national labs, have unveiled a new online platform aimed at assisting utilities in comprehending the impacts of solar energy projects on their power systems. This resource is poised to bolster utilities’ confidence in expanding their solar portfolios, thereby ensuring the reliable delivery of electricity while bolstering U.S. efforts to combat climate change.
“This web portal and its array of functionalities represent a significant advancement for the power systems analysis research and development community, ultimately enhancing the reliability and resilience of the electricity grid as we strive to integrate more renewable energy sources,” remarked Jin Dong, the lead researcher at ORNL.
The newly introduced software platform, named the Open Energy Data Initiative Solar Systems Integration Data and Modeling, stands out from previous data repositories due to its accessibility; it is freely available for use by any user with any power system datasets. Developed collaboratively with Argonne National Laboratory, Pacific Northwest National Laboratory, and the National Renewable Energy Laboratory, this online portal enables utilities and other stakeholders to leverage their own algorithms and data for analyzing electric grids with substantial solar projects. This is particularly crucial as solar resources are often geographically dispersed among various owners, limiting utilities’ access to comprehensive information required for accurate system behavior assessment.
“While renewable technology is readily available, many utilities are apprehensive about managing systems with high renewable penetration. Through this software platform, they can expedite the adoption process,” Dong emphasized.
The platform encompasses four key applications:
1. Pre-processing data to safeguard privacy by anonymizing personal details and consolidating information from diverse network technologies into a unified dataset. 2. Developing algorithms to accurately infer electrical voltage across the entire network with minimal input. 3. Designing intelligent control systems to optimize solar energy device management and enhance grid reliability while maximizing renewable energy utilization. 4. Creating algorithms capable of detecting deviations in electric current, voltage, or frequency, thereby identifying indicators of abnormal grid behavior that could trigger cascading failures.
In addition to the framework and algorithms, ORNL has crafted a case study demonstrating the toolkit’s efficacy in detecting transient grid faults, with the collaboration of University of Tennessee-ORNL Governor’s Chair Yilu Liu and her team.
Moving forward, researchers are exploring enhancements to the software, such as evaluating the impact of electric vehicle charging scenarios or emerging “smart building” technologies. Dong highlighted the importance of empowering utilities to adapt their planning tools using these resources to address evolving energy needs effectively.
